BENGUET FOREST FIRE BURNED AREA & TAAL ASH EXTENT ESTIMATION USING SUPPORT VECTOR MACHINE & THRESHOLDING TECHNIQUES Arlo Jayson Sabuito (1), Cara Patricia Canlas (1), Mark Jayson Felix (1) Gay Jane Perez (1) 1 Institute of Environmental Science and Meteorology, University of the Philippines, Diliman, Quezon City, 1101, Metro Manila, Philippines Email:
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[email protected] KEY WORDS: Diwata-2, Support Vector Machine, Burned Area Index, Forest Fire, Ashfall Extent ABSTRACT: Diwata-2 is the second Philippine microsatellite developed to provide Earth- observation data for disaster assessment and environmental monitoring. Since its launch in October 2018, the satellite has collected 25,811 images for various applications. In this study, the capability of Diwata-2 to monitor large-scale disasters is demonstrated through the identification of ash-stricken areas in the recent Taal Phreatic eruption and forest fire-affected areas of Benguet. Ashfall and burned area extent were classified from the Taal volcano eruption and Benguet forest fire, respectively. Diwata-2 images used were taken on January 6, 2020 and January 27, 2020 capturing the volcano’s surrounding areas, and February 29, 2020 for areas in Benguet Province. The extent of both disasters’ damages was delineated through index difference thresholding and Support Vector Machine (SVM) classification. For the index difference thresholding, Normalized Difference Vegetation Index (NDVI) and Burned Area Index (BAI) were used to identify ash stricken and burned areas, respectively. Similar methods were applied to Sentinel-2 for further evaluation using a higher resolution optical imagery. The ashfall extent measured from Diwata-2 was estimated at 20,359.64 ha and 55,669.24 ha for NDVI thresholding and SVM classification, respectively.